code: def __init__(
      self,
      model: torch.nn.Module,
      config_list: List[Dict],
      evaluator: Evaluator,
      training_steps: int,
  ):
      ...
  
imports: from __future__ import annotations
  from collections import defaultdict
  import functools
  import logging
  from typing import Callable, Dict, List, Literal, Tuple, overload
  import torch
  from .tools import _METRICS, _MASKS, norm_metrics, generate_sparsity, is_active_target
  from ..base.compressor import Compressor, Pruner
  from ..base.target_space import TargetType
  from ..base.wrapper import ModuleWrapper
  from ..utils.docstring import _EVALUATOR_DOCSTRING
  from ..utils.evaluator import Evaluator, TensorHook
label_desc: Use image node_id 1 to create a new TaylorPruner object from inherited base classes: Pruner with example: obj = TaylorPruner(model, config_list, evaluator, training_steps)